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检索条件"任意字段=2023 3rd International Conference on Electrical Engineering and Computer Technology, ICEECT 2023"

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Control of DVR Using Multilayer Gamma Filter Under Non-Ideal Grid Conditions 3

Control of DVR Using Multilayer Gamma Filter Under Non-Ideal...

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3rd IEEE international conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

作者： Nagamalleswari, Vemireddy Arya, Sabha Raj Rajagopal, V. Sardhar Vallabhbhai National Institute of Technology Department of Electrical Engineering Surat395007 India Kakatiya Institute of Technology & Science Department of Ee Engineering Warangal506015 India

ISBN: (纸本)9798350319972

This paper investigates dynamic voltage restorers (DVRs) as a solution to voltage-based power quality issues. A control algorithm based on a Multilayer Gamma Filter is proposed to compensate for voltage sag, voltage swell, distortions, and phase voltage discrepancies caused by various factors in series-connected devices. To improve power quality, the proposed Multilayer Gamma Filter-based control algorithm is used for the compensator. In several ways, the Multilayer Gamma Filter outperforms traditional filter designs. To begin with, it is adaptive, which means it can change its parameters in response to various types of disturbances. Second, it has a lower computational complexity than other filters, making it a more efficient option for real-time applications. Finally, it has a high accuracy in estimating input signal parameters and a fast transient response. The system performs satisfactorily even under less-than-ideal conditions with wide voltage and load variations. The control algorithm employs two proportional integral (PI) gains to maintain the dc link voltage and terminal voltage stable. The gains of the PI controllers are critical for estimating reference load voltages correctly. The salp swarm optimization algorithm is used to optimize DVR gains. The salp swarm optimization algorithm has been demonstrated to be effective in PI tuning, providing faster convergence and improved performance over traditional tuning methods. The control system can achieve better regulation of the process variable and overall system performance by optimizing the PI gains. The optimized gains are applied to a fourth-order multilayer gamma filter to extract reference load voltages. To extract reference load voltages, the optimized gains are applied to a fourth-order multilayer gamma filter. © 2023 IEEE.

关键词： Multilayers

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The Usefulness and Students' Perception of TikTok Application as a Learning Tool in Higher Education 3

The Usefulness and Students' Perception of TikTok Applicatio...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Che Lah, Noor Hidayah Eriansah, Jasrey Raznizar Mustafa, Wan Azani Hanafi, Hafizul Fahri Ghani, Miharaini Md Al-Jawahry, Hassan M. Hamizan, Muhamamad Hamirul Hashim, Suhaizal Jumaat, Nurul Farhana Almoussawi, Zainab Abed Universiti Pendidikan Sultan Idris Faculty of Computing and Meta-Technology Perak Tanjong Malim Malaysia Universiti Malaysia Perlis Faculty of Electrical Engineering Technology UniCITI Alam Campus Sungai Chuchuh Perlis Padang Besar Malaysia Universiti Putra Malaysia Faculty of Modern Language and Communication Department of Communication Malaysia The Islamic University Najaf Faculty of Engineering Iraq Universiti Pendidikan Sultan Idris Faculty of Computing and Meta-Technology Malaysia Universiti Tun Hussein Onn Faculty of Technical and Vocational Malaysia School of Education Universiti Teknologi Malaysia College of Islamic Science Ahl Al Bayt University Karbala Iraq

ISBN: (纸本)9798350317022

Numerous tools, such as Google Meet, Microsoft Team, Zoom, Skype, Google Hangout, and social media, have been utilized for online learning. TikTok is one social media that can be used for online learning. TikTok is a unique application that can be productively used for online learning processes. However, there's a lack of research to examine the usefulness of TikTok applications for online learning within Malaysian samples. Therefore, this study aims to identify the usefulness of TikTok as a learning tool and investigate the students' perceptions of online learning using TikTok in one education University in Malaysia. This study employed a cross-sectional survey as its research design as part of the quantitative research methodology. Note that 317 students enrolled in one education university in Malaysia make up the sample for this study. The questionnaire has been validated by two professionals. The results revealed that students have a positive perception of the usefulness of TikTok in online learning. The suggested approach achieved the mean of 3.924 and standard deviation of 0.918 in for the students' perception. In addition, the findings of this study also show that perceived information value using TikTok in online learning has the highest mean value. © 2023 IEEE.

关键词： higher education online learning social media students Tiktok

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Tuning and Optimization of Temperature in a Fatigue Sodium Loop of Fast Breeder Tank Reactor Using PID Controller 3

Tuning and Optimization of Temperature in a Fatigue Sodium L...

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Mohan M, Madhan Vijayachitra, S. Karthikeyan, M. Vincent, J. Joseph, J Alwin Kongu Engineering College Department of Electrical and Instrumentation Engineering Erode India Kongu Engineering College Department of Control and Instrumentation Engineering Erode India Indira Gandhi Centre for Atomic Research Department of Insot Kalpakkam India

ISBN: (纸本)9798350322842

Sodium-based heat transfer technology development in India for fast-breeder nuclear reactors utilizes liquid sodium metal as a coolant because it can remove heat efficiently. In the secondary loop of the Fast Breeder Tank Reactor, liquid sodium exchange heat from the nuclear reactor to water through the pipe arrangement to produce superheated steam for power generation. Sodium has a high boiling point of 882.8°C, low-melting-point of 97.7°C helps to operate the plant under low pressure of around 0.1 MPa. Sodium evolved as the solid state at ambient temperature and transferred to liquid state above 550°C. Metallic sodium has a high reactivity in chemical reactions with metallic flow pipe exposed to moisture or periodical environmental conditions. An important built-up material of liquid sodium was very effective heat exchanging capacity within a short period. Due to sodium's wonderful structural and chemical behavior, it forms the appropriate choice for heat exchanger or as coolant in the standard nuclear power plant fast breeder reactor (FBR). Fatigue Loop Testing Method is used to analyze the purity property of sodium to predict the corrosion of structural materials and blockage of flow routes in the secondary loop of the Fast Breeder Tank Reactor(FBTR) loop in the Nuclear power plant at Kalpakkam. The fatigue loop test requires an appropriate PID controller design to set the sodium flow control in pipes at an optimized temperature to maintain its liquid state for thermal transmission and the necessary pressure to apply through the electromagnetic pump to monitor sodium purity, system performance, accuracy and efficiency. Here, the optimum temperature for the operation of the Fast Breeder Tank Reactor (FBTR) tuned in the Fatigue loop is simulated using the PID Auto Tuning method. © 2023 IEEE.

关键词： Sodium

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An Energy-Efficient Metaheuristic for Offloading Security-Critical Tasks in Mobile Edge Computing with Integrated DPUs 3

An Energy-Efficient Metaheuristic for Offloading Security-Cr...

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3rd IEEE international conference on Intelligent technology and Embedded Systems, ICITES 2023

作者： Hong, Shaoying Zhu, Jiayin Yuan, Yiqi Sun, Jin School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China International Joint Audit Institute Nanjing Audit Technology Nanjing211815 China

ISBN: (纸本)9798350343755

In mobile edge computing (MEC) paradigm, for the security-critical computation tasks offloaded from the mobile device, the MEC server needs to decrypt the encrypted task data before task execution, leading to heavy computation load on the CPUs of the MEC server. The integration of data processing unit (DPU) into the MEC server can release CPUs from data decrpytion for the purpose of reducing computation and energy overheads. This paper studies a task offloading problem in a MEC system with integrated DPUs, which aims at reducing the total energy consumption under the deadline constraint on task completion time. We formulate the studied problem as an combinatorial optimization model and propose a group mapping-based cuckoo search (GMCS) metaheuristic algorithm to explore high-quality energy-efficient solutions to the formulated model. The proposed GMCS introduces a group mapping operator and a greedy-based task offloading strategy for converting cuckoo individuals into offloading solutions and evaluating the objective values of the converted solutions, respectively. We provide a theoretical analysis to justify that the mapping operator can improve the diversity of the converted solutions and in turn the metaheuristic’s searching capability. We create various testing instances for a MEC system equipped with DPUs to demonstrate the proposed GMCS produces high-quality solutions to the studied offloading problem, with reduced energy consumption compared with baseline algorithms. © 2023 IEEE.

关键词： Mobile edge computing

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Interleaved Boost Converter (IBC) based fast EV charging system: Design and Simulation 3

Interleaved Boost Converter (IBC) based fast EV charging sys...

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3rd IEEE international conference on Smart Technologies for Power, Energy and Control, STPEC 2023

作者： Marothiya, Anirudha S. Chaturvedi, Pradyumn Chaudhari, M.A. Vnit Electrical Engineering Dept Nagpur India Bajaj Institute of Technology Electrical Engineering Dept Wardha India

ISBN: (纸本)9798350304732

Transportation system is considered to be one of the most important aspect for a developing nation irrespective of its mode (road, railway, air, and water). The development is more appreciated when it will be in collaboration with nature. Electrification in transportation system is a promising area where various problems of existing transportation system were addressed such as less noise, reduce the import of petroleum products and improve the quality of air. The main problem with electric transportation (mainly electric vehicles) is overnight charging. To meet this, different types of fast chargers were designed and developed in last couple of years based on fundamental converter topologies such as: phase shift full bridge (PSFB) converters, LLC resonant converter, dual active bridge (DAB) converter, CLLC converters, and DC-DC boost converters. However, various limitations of the existing converters such as: high switching losses, large inductor size and high electromagnetic interference have motivated researchers to develop novel converter topology. The interleaved boost converter (IBC) based power electronic circuits are finding huge application in fast charging of EVs because of many advantages over fundamental boost converters in terms of low ripples in input current and output voltage, high efficiency, and low switching losses. In this research article, an IBC based 26kW fast charging system for EV is designed and simulated in MATLAB environment. Mathematical analysis of IBC in various modes of operation along with design parameters are well explained. A Nissan leaf 2013 model battery pack specifications where considered for simulation. Further, proportional integral (PI) controllers are applied to control EV battery parameters in constant current (CC) mode and constant voltage (CV) mode depending upon the state of charge (SOC) of EV battery. © 2023 IEEE.

关键词： constant current (CC) constant voltage (CV) and proportional integral (PI) Electric vehicle (EV) interleaved boost converter (IBC)

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Battery Energy Management Systems in Active Distribution Network 3

Battery Energy Management Systems in Active Distribution Net...

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Shrivastava, Anurag Raturi, Anuj Gupta, Hemant Rao, Aln Singh, Surendra Sankhyan, Akhil Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Graphic Era Deemed to Be University Department of Mechanical Engineering Uttarakhand Dehradun India Gla University Department of Electrical Engineering Mathura India Lloyd Institute of Engineering and Technology Department of CSE Greater Noida India Quantum University Uttarakhand Roorkee India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350322842

Battery Energy Management Systems (BEMS) have gained prominence in recent years as a result of the demand for renewable resources sources an imperative for efficient Mechanisms for storing energy. BEMS plays a critical role in optimizing battery usage, extending battery life, reducing operating costs, and ensuring grid stability. This paper proposes a BEMS for an active distribution network that uses Support Vector Machines (SVMs) to forecast energy consumption and generation. The proposed BEMS integrates a force or management system, as well as a battery management, which work together to manage battery energy storage and optimize energy flows within the network. The SVM algorithm is used to predict the energy consumption and generation patterns of the network, based on historical data and weather forecasts. The BEMS uses this information to determine the optimal battery charge and discharge schedules, which balance energy supply and demand, while minimizing the cost of energy consumption. BEMS is deployed as planned and tested on a simulated active circulation system, which consists of a PV system, a wind turbine, and a battery storage system. The simulation According to the obtained BEMS is useful for optimizing battery energy usage and reducing operating costs, while maintaining grid stability. Overall, this article provides a detailed study on development and deployment of a BEMS for an active distribution network, using SVMs to forecast energy consumption and generation. The proposed BEMS provides a cost-effective solution for optimizing battery energy storage and improving the overall efficiency and reliability of the network. © 2023 IEEE.

关键词： Support vector machines

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A K-means Clustering Method for Fuzzy Neighborhood Granules 3

A K-means Clustering Method for Fuzzy Neighborhood Granules

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3rd IEEE international conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Guo, Kai Li, Guohe Li, Zheng Pan, Xueling Yin, Wangping College of Information Science and Engineering Beijing China Karamay Campus Department of Computer Science Karamay China

ISBN: (纸本)9781665490788

K-means algorithm is a typical distance-based clustering analysis algorithm, and the neighborhood granular K-means clustering algorithm uses the neighborhood granulation technique on its basis to solve the problem of poor clustering of the K-means clustering algorithm on non-linear separable datasets. However, the use of neighborhood relations in the granulation lead to the inability of the algorithm to deal with outliers effectively, resulting in some samples being misclassified. By introducing the concept of fuzzy set and combining granular computing theory, a new neighborhood granular K-means clustering method is proposed, where samples are constructed using fuzzy neighborhood granularity technique to construct fuzzy neighborhood granules, and the membership between samples is used for neighborhood granularity instead of clear neighborhood relations, which reduces the impact of outliers. A new distance measure for fuzzy neighborhood granules is proposed based on the size and form of the fuzzy neighborhood granules, which reduces the computational complexity. In addition, the algorithm combines the idea of K Nearest Neighbor to define a neighborhood threshold metric that adaptively generates neighborhood thresholds for any data set. It considers the size of the data set objectively and reduces the subjective influence of manual selection of neighborhood threshold. Finally, the Accuracy and Fowlkes Mallows Index values of the algorithm are increased by 6.4 %, 9.21%, 3.5%, and 7.89% on the synthetic data set and UCI data set, respectively, and increased by 8.65% and 9.43% on the seismic facies lithology identification data set, respectively. The experimental results prove the feasibility and effectiveness of the fuzzy neighborhood granular K-means clustering method. © 2023 IEEE.

关键词： K-means clustering

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Framework for the Deployment of Intelligent Smart Cities (ISC) using Artificial Intelligence and Software Networking Technologies 3

Framework for the Deployment of Intelligent Smart Cities (IS...

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3rd international conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Mohamed, Nachaat Upadhyay, Ramakant Jakka, Geethamanikanta Rambabu, P.V. Alfurhood, Badria Sulaiman Singh, Devesh Pratap Universiti Sains Malaysia Rabdan Academy UAE Homeland Security Abu Dhabi United Arab Emirates Sanskriti University Department of CSE Mathura Uttar Pradesh India University of the Cumberlands Data Analytics Information Technology United States Civil Engineering Princess Nourah Bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences Saudi Arabia

ISBN: (纸本)9798350399264

This article's goals include providing a framework for interpersonal and communication to safeguard welfare services and assess how well the innovation ecosystem is now understood. An essay starts with an overview or description of "urban area"This viewpoint includes neighborhood services, modern amenities, or smart infrastructure. Information and technology, digital operations use, monitoring, and interconnection, amongst other things. The section that follows examines various urban planning concerns, either administration or expansion. Utilizing diverse technologies effectively is made possible by innovative information about towns or an answer to a question concerning high-quality public infrastructure. An innovative method of managing networks is the Software Defined Network (SDN) architecture. Unlike switches in a conventional network computing environment, changes in SDN do not process inbound sachets in the similar means. If no inbound packets are identified after searching the linking tables, they are passed to the control system, the SDN's operating system, for processing. A Spread Denial of Service (DoS) outbreak poses the biggest risk to the cyber security of an SDN *** system or application layers of the disease-ridden devices connected to the system will be the target of the attack. The approach for determining whether incoming packets are contaminated or not is clever machine learning-based, and it is proposed in this paper. In the context of smart cities, the deployment of artificial intelligence (AI) has newly drawn more and more attention. The purpose of this study is to perform a works assessment to examine the role of AI in the various parts of smart towns given the relevance of the topic. This study's technique combines a thorough literature evaluation to find the most pertinent papers with reference system investigation to reveal the subtleties of the subject. The findings of this study highlight the significance of this technology, whic

关键词： Smart city

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Securing Patient Information in Connected Healthcare Systems in the Age of Pervasive Data Collection 3

Securing Patient Information in Connected Healthcare Systems...

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3rd IEEE international Mediterranean conference on Communications and Networking, MeditCom 2023

作者： Dimitrievski, Ace Loncar-Turukalo, Tatjana Trajkovik, Vladimir Faculty of Computer Science and Engineering Skopje Macedonia University of Novi Sad Centre of Excellence for Vibro-Acoustic Systems and Signal Processing Faculty of Technical Sciences Serbia

ISBN: (纸本)9798350333732

This paper explores the ethical and security challenges of integrating Internet of Things technologies into health-care systems. We examine real-world ethical dilemmas, including privacy and security of personal and medical data. We also analyze security in connected healthcare systems, focusing on securing data transmission, preventing data exfiltration, and mitigating the risk of de-anonymization of data. We propose a fog-based architecture and data avoidance principle to address and minimize the risks to patient data, intending to navigate the ethical landscape of IoT in healthcare, ensuring patient privacy. © 2023 IEEE.

关键词： Data privacy

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Research on Big Data of Vocational Education Based on Simhash Algorithm 3rd

Research on Big Data of Vocational Education Based on Simhas...

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3rd EAI international conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023

作者： Sun, Xuefeng Xue, Jin Luo, Jiawei Song, Limei Dalian University of Science and Technology Liaoning Dalian116052 China Shandong Institute of Commerce and Technology Shandong Jinan250103 China

ISBN: (纸本)9783031631320

The quality assurance of higher vocational education is an important measure to expand the supply of high-quality vocational education and realize the connotative development of higher vocational education. However, the quality assurance of higher vocational education needs to be clarified in theory and mode and optimized and improved in practice in terms of who will guarantee, what to guarantee and how to guarantee. The research on vocational education big data based on simhash algorithm is a research on simulation model. It uses the characteristics of big data to simulate and analyze individual behavior. In this way, it can be used as a tool to analyze and predict social phenomena. It has been widely used in many fields of economics, sociology, psychology and so on. The research on big data of vocational education based on simhash algorithm is very easy to use, because it is just like using Excel or other spreadsheet software. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Big data

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